Legged Robots Research Articles

Environmental Adaptability of Legged Robots with Cutaneous Inflation and Sensation

In this article, a novel approach to enhance the maneuverability and adaptability of legged robots in challenging environments is proposed. This approach involves the integration of soft inflatable sensing skin, which provides additional mobile modes and environmental adaptability. The inflated skin's structural properties, such as buoyancy, volumed shape, and physical compliance, enable quadruped robots to extend their mobility to stable swimming and crawling modes. The inflated skin also offers physical protection through cushioning and backing effects, allowing robots to roll down stair‐like structures. Furthermore, the integration of tactile sensors provides the host robot with accurate and intuitive contact information, enabling increased environmental adaptability and responsive behavior. The robot can protect itself from impacts, detect and detour obstacles, and dynamically interact with its surrounding environment. Overall, the proposed approach offers a synergistic integration of soft inflatable sensing skin and tactile sensors to enhance legged robots’ maneuverability and adaptability in harsh environments. The integrated system enables robots to achieve challenging missions, extending their capabilities beyond conventional locomotive modes. The proposed approach has significant potential applications in fields such as search and rescue, surveillance, and exploration.

Energy Efficiency and Performance Evaluation of an Exterior-Rotor Brushless DC Motor and Drive System across the Full Operating Range

In recent years, exterior-rotor brushless DC motors have become increasingly popular in robotics applications due to their compact shape and high torque density. However, these motors were originally used for continuous operation in drones. For applications such as exoskeletons, prostheses, or legged robots, short bursts of high power are often required. Unfortunately, vendors do not typically provide data on the motors’ performance under these conditions. This paper presents experimental data on the torque–speed relationship, efficiency, and thermal responses of one of the most widely used outrunner-type brushless motors across its full operating range, including high-power short-duration operation. The results of this study can inform the selection and design of actuators for a range of robotics applications, particularly those that require high power output for brief periods of time.

Design and Experiments of a Human-Leg-Inspired Omnidirectional Robotic Leg

Design and Experiments of a Human-Leg-Inspired Omnidirectional Robotic Leg

Inverse-Dynamics MPC via Nullspace Resolution

Optimal control (OC) using inverse dynamics provides numerical benefits, such as coarse optimization, cheaper computation of derivatives, and a high convergence rate. However, to take advantage of these benefits in model predictive control (MPC) for legged robots, it is crucial to handle efficiently its large number of equality constraints. To accomplish this, we first propose a novel approach to handle equality constraints based on nullspace parameterization. Our approach balances optimality, and both dynamics and equality-constraint feasibility appropriately, which increases the basin of attraction to high-quality local minima. To do so, we modify our feasibility-driven search by incorporating a merit function. Furthermore, we introduce a condensed formulation of inverse dynamics that considers arbitrary actuator models. We also propose a novel MPC based on inverse dynamics within a perceptive locomotion framework. Finally, we present a theoretical comparison of OC with forward and inverse dynamics and evaluate both numerically. Our approach enables the first application of inverse-dynamics MPC on hardware, resulting in the state-of-the-art dynamic climbing on the ANYmal robot. We benchmark it over a wide range of robotics problems and generate agile and complex maneuvers. We show the computational reduction of our nullspace resolution and condensed formulation (up to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">${47.3}\boldsymbol{\%}$</tex-math></inline-formula> ). We provide evidence of the benefits of our approach by solving coarse optimization problems with a high convergence rate (up to 10 Hz of discretization). Our algorithm is publicly available inside <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Crocoddyl</small> .

Analysis of motion characteristics of lower limb exoskeleton robot

To address the issue of motion coordination in lower limb exoskeleton rehabilitation robots, and to meet the basic characteristics of ergonomics and human kinematics, a humanoid design was adopted to design a lower limb exoskeleton rehabilitation robot. The Denavit- Hartenberg (D-H) mathematical model of the lower limb exoskeleton rehabilitation robot was established, and the motion characteristics of each joint were analyzed to obtain the D-H parameters during the motion process. The motion characteristics were analyzed from the perspectives of forward kinematics and inverse kinematics. The variation law of motion parameters during the motion process was obtained, and simulation analysis of the motion characteristics was performed. The results show that the maximum center of mass velocity is 0.45 m/s, which is reached within 0.8 seconds. After that, the velocity decreases, with a range of approximately -0.2 m/s to 0.55 m/s. It can be seen that the displacement and velocity changes of the exoskeleton robot legs are relatively stable, which meets the design requirements.

Implementation of Grid Mapping Method for Firefighting Legged Robot

The firefighting robot contest is an event to encourage high education students to explore electronics and robotic skill. The difficulty level of the contest increases from year to year though the arena layout is relatively similar. The field of arena consists of maze, detachable doors and distractorswhich requires smart idea to enable the robot to be well-performed. The combination of home position and random fire spot at each round of the game make each team have to find the most effective method to win the match. This paper presents an implementation the grid map method on the Azmi four legged robot using ultrasonic PING sensor, GPYA021 infrared sensor and GY-955 gyroscope. An ultrasonic sensor is attached on each of four sides of the robot. The data from each sensor will be interpreted as the distance of the front, right, left and back of the robot relative to the wall. Interpretation depends on the robot's current position. Virtual mapping technique was used by assuming that the arena consists of grids which have uniform size. Each grid was given a consecutive index numbering i.e a symbolic number which in practice be manifested in terms of distance unit. The results showed that the grid map method in this study worked well, tested on four randomized configurations, the robot successfully carried out the search task and returned to the home position with an acceptable execution time.

RANCANG BANGUN MODUL UKUR TEKANAN PIJAK TELAPAK KAKI ROBOT HUMANOID

Maintaining balance for humanoid robots is one of the core problems to be solved. Krakatau FC as a humanoid type robot performs balancing based on error information obtained from the IMU sensor. Information from the IMU alone is considered inadequate because it ignores the contours of the robot's stepping area which greatly influences the actions that must be taken to maintain balance. The focus of this research is to create a foot pressure measurement module that is compatible with the Dynamixel communication protocol. The sensor used to measure pressure is a Force Sensitive Resistor (FSR) sensor. The test results show the module's ability to measure the pressure exerted by the robot's legs and communicate with the robot's main controller using the Dynamixel protocol. From the test, it is also known that the modules made can help the robot's mechanical calibration process based on the comparison of the pressure between the right and left soles of the feet.

Flexible & Stretchable EMG Sensor for Lower Extremity Amputee.

EMG signals can be widely used for indicators of muscle activity, and it can be used for robot control. However, the practical use of the EMG sensor for the amputee has been limited due to harsh conditions in the socket where strong pressure and friction exist. In this paper, thus we suggested a flexible and stretchable EMG Sensor. It is designed to withstand the pressure of the socket and to be used repeatedly with soft adhesive material. The performance of mechanical and electrical properties is investigated, and the muscle signals are recorded in static and dynamic (jump and gait) conditions. The selectivity of the recorded muscle signals during dorsiflexion and plantar flexion shows better than that of commercial electrodes indicating that it could be used for control of robotic legs in the future.Clinical Relevance- The flexible material and stretchable electrode pattern could be helpful in clinical research for an amputee.

Torque-Based Control of a Bio-Inspired Modular Climbing Robot

This article presents a generalizable, low computational cost, simple, and fast gravity compensation method for legged robots with a variable number of legs. It is based on the static problem, which is a reduction in the dynamic model of the robot that takes advantage of the low velocity of climbing robots. To solve it, we propose a method that computes the torque to be applied by each actuator to compensate for the gravitational forces without using the Jacobian matrix for the forces exerted by the end-effector and without using analytical methods for the gravitational components of the model. We compare our method with the most popular method and conclude that ours is twice as fast. Using the proposed gravity compensator, we present a torque-based PD controller for the position of the leg modules, and a body velocity control without dynamic compensation. In addition, we validate the method with both hardware and a simulated version of the ROMERIN robot, a modular legged and climbing robot. Furthermore, we compare our controller with the usual kinematic inverse controllers, demonstrating that the mean angular and linear error is significantly reduced, as well as the power requirements of the actuators.

Scientific exploration of challenging planetary analog environments with a team of legged robots

The interest in exploring planetary bodies for scientific investigation and in situ resource utilization is ever-rising. Yet, many sites of interest are inaccessible to state-of-the-art planetary exploration robots because of the robots’ inability to traverse steep slopes, unstructured terrain, and loose soil. In addition, current single-robot approaches only allow a limited exploration speed and a single set of skills. Here, we present a team of legged robots with complementary skills for exploration missions in challenging planetary analog environments. We equipped the robots with an efficient locomotion controller, a mapping pipeline for online and postmission visualization, instance segmentation to highlight scientific targets, and scientific instruments for remote and in situ investigation. Furthermore, we integrated a robotic arm on one of the robots to enable high-precision measurements. Legged robots can swiftly navigate representative terrains, such as granular slopes beyond 25°, loose soil, and unstructured terrain, highlighting their advantages compared with wheeled rover systems. We successfully verified the approach in analog deployments at the Beyond Gravity ExoMars rover test bed, in a quarry in Switzerland, and at the Space Resources Challenge in Luxembourg. Our results show that a team of legged robots with advanced locomotion, perception, and measurement skills, as well as task-level autonomy, can conduct successful, effective missions in a short time. Our approach enables the scientific exploration of planetary target sites that are currently out of human and robotic reach.

Learning Complex Motor Skills for Legged Robot Fall Recovery

Falling is inevitable for legged robots in challenging real-world scenarios, where environments are unstructured and situations are unpredictable, such as uneven terrain in the wild. Hence, to recover from falls and achieve all-terrain traversability, it is essential for intelligent robots to possess the complex motor skills required to resume operation. To go beyond the limitation of handcrafted control, we investigated a deep reinforcement learning approach to learn generalized feedback-control policies for fall recovery that are robust to external disturbances. We proposed a design guideline for selecting key states for initialization, including a comparison to the random state initialization. The proposed learning-based pipeline is applicable to different robot models and their corner cases, including both small-/large-size bipeds and quadrupeds. Further, we show that the learned fall recovery policies are hardware-feasible and can be implemented on real robots.

Design of Single Legged Hopper Robot in Gazebo

Abstract: Robotics is one of the core areas where the bioinspiration is frequently used to design various engineered morphologies to develop novel behavioral controllers comparable to human being and animals. Research on legged robots has been going on for over a century. The reason behind such sustained interest in legged robots is due to the fact that most of the earth’s land surface is inaccessible to wheeled or tracked systems. Legged animals can, however, be found everywhere. Thus, mankind has been fascinated with the idea of a mobile legged robot that can handle difficult terrain and be useful in the fields of transportation, forestry, agriculture, fire, fighting, hazardous areas, defense (carrying weapons to soldiers, de-mining), police purposes, assistive devices for walking, entertainment (toy production), robotic pets, and ocean and space exploration. Our project is based on one such example, single legged hopper robot a legged locomotive inspired by the jumping mechanism of click beetles. It aims to create a single legged hopper robot in Gazebo. A simulation tool that offers the ability to accurately, and efficiently, simulate populations of robots in complex indoor and outdoor environments. The Robot Operating System (ROS) works best in the LINUX OS, is the software of version Melodic + Gazebo 9, is utilized in the project.

Research on Walking Gait Planning and Simulation of a Novel Hybrid Biped Robot

A kinematics analysis of a new hybrid mechanical leg suitable for bipedal robots was carried out and the gait of the robot walking on flat ground was planned. Firstly, the kinematics of the hybrid mechanical leg were analyzed and the applicable relevant models were established. Secondly, based on the preliminary motion requirements, the inverted pendulum model was used to divide the robot walking into three stages for gait planning: mid-step, start and stop. In the three stages of robot walking, the forward and lateral robot centroid motion trajectories and the swinging leg joint trajectories were calculated. Finally, dynamic simulation software was used to simulate the virtual prototype of the robot, achieving its stable walking on flat ground in the virtual environment, and verifying the feasibility of the mechanism design and gait planning. This study provides a reference for the gait planning of hybrid mechanical legged bipedal robots and lays the foundation for further research on the robots involved in this thesis.

Online Feet Potential Fields for Quadruped Robots Navigation in Harsh Terrains

Quadruped robots have garnered significant attention in recent years due to their ability to navigate through challenging terrains. Among the various environments, agriculture fields are particularly difficult for legged robots, given the variability of soil types and conditions. To address this issue, this study proposes a novel navigation strategy that utilizes ground reaction forces to calculate online artificial potential fields, which are then applied to the robot’s feet to avoid low-traversability regions. The strategy also incorporates the net vector of the attractive potential field towards the goal and the repulsive field to avoid slippery regions, which dynamically adjusts the quadruped’s gait. A realistic simulation environment validates the proposed navigation framework with case studies on randomly generated terrains. A comprehensive comparison with baseline navigation methods is conducted to assess the effectiveness of the proposed approach.

Hexapod Robot Movement Control for Uneven Terrain

Hexapod robot is a robot that has 6 legs with joints or structures that resemble insect legs. This study uses the inverse kinematic method with the aim of finding points and effectors of the robot's legs that will make the robot's legs pass through uneven obstacles such as uneven flor, stairs, bolong-bolong obstacles, bolong-non-obvious obstacles and non-objective obstacles. This inverse kinematic is accessed with the Open Cm 9.04 microcontroller to control the dynamixel servo on the robot leg. The results of testing the robot's movement using inverse kinematics have succeeded in overcoming uneven obstacles using the inverse kinematic method. For testing the stability of the robot it is still not stable enough because the mechanical part of the foot is still not precise. The conclusion of the study, from 6 trials that average and uneven obstacles were obtained in the range of 85% - 95%. The inverse kinematic method using a proximity sensor on the front of the robot, the average success that can be obtained is in the range of 80% - 90%.

Spatial Repetitive Impedance Learning Control for Robot-Assisted Rehabilitation

In robot-assisted rehabilitation and leg exoskeletons, humans and robots are required to collaboratively complete repetitive tasks with fixed periodic paths. In such applications, impedance learning control can provide variable impedance regulation for improving the performance of physical interactions; however, designing such control is highly challenging owing to the difficulty in modeling human time-varying dynamics. By exploiting the spatial periodicity characteristics of the desired trajectory and human impedance, we propose a novel spatial repetitive impedance learning control strategy to enhance interaction performance. First, a defined spatial operator serves as the mathematics foundation for constructing the robot dynamics in the spatial domain. Then, a spatial impedance learning controller is designed. In this article, time-varying impedance profiles are estimated using spatial full-saturation iterative learning laws, while robotic parameter uncertainties are estimated using the differential adaptation law with projection modification. We validate the uniform convergence of the tracking error through a Lyapunov-like analysis and demonstrate the control effectiveness using an illustrative example. Compared with related results on temporal repetitive learning control, the proposed control approach can enable human–robot system to complete a repetitive task with unspecified speeds according to the users' strengths and motion capacity.

Quadruped Capturability and Push Recovery via a Switched-Systems Characterization of Dynamic Balance

This article studies capturability and push recovery for quadruped locomotion. Despite the rich literature on capturability analysis and push recovery for legged robots, existing tools have been developed mainly with the requirement of reaching static or quasi-static balance following a push. In practice, this requirement commonly restricts capturability analysis to cases with simple dynamics and fails to encode the time dependence of capturable states for legged locomotion with time-based gaits. To address these issues, we apply switched systems to model quadruped locomotion and extend capturability notions through a novel specification of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">dynamic balance</i> . We also provide an explicit model predictive control (EMPC) scheme to compute the dynamic balance and capturable tubes and offer a way of using the capturable tube to synthesize push recovery controllers. Such a generalization allows for a rigorous characterization of disturbance timing on the capturability of quadrupedal locomotion and opens the door of disturbance-timing-aware push recovery control strategies. Extensive simulation and hardware experiments illustrate the necessity of considering dynamic balance for quadrupedal push recovery, reveal how disturbance timing affects capturability, and demonstrate the significant improvement in disturbance rejection with the proposed strategy. Hardware experimental validations on a replica of the Mini Cheetah quadruped further verify that the proposed approach performs statistically better than the state-of-the-art baseline considered.

Footholds optimization for legged robots walking on complex terrain

Footholds optimization for legged robots walking on complex terrain

The Design of a New 3D Print-in-place Soft Four-Legged Robots with Artificial Intelligence

Soft and flexible robots are designed to change their flexibility over a wide range to perform tasks adequately in real-world applications. Current soft robots require cast moulding, high assembly effort and large actuators. Soft origami structures exhibit high levels of compliance. In this paper, we designed a new 3D print-in-place soft four-legged robot (3DSOLR). Our soft legged robot is an endurance application adapted from the soft origami zigzag gripper. This novel and innovative design are inspired by the rigid joint Theo Jansen legged robot with highly adaptive 3D print-in-place soft origami legs capable of fluid motion and even surviving drop tests. The robot mechanism consists of four soft origami flexible legs driven by two DC motors. The 3DSOLR is lightweight and semi-autonomous using two Hall effect sensors and a wireless Bluetooth module. Being 3D print-in-place using Thermoplastic polyurethane also increases its durability while having flexibility, simplicity and safety. The robot also has a gripper inspired by the mandible of male European stag beetle (Lucanus cervus). These features make this robot suitable to be used in social robotics and rescue robotics applications. The transmitter program is implemented in Bluetooth serial communication using MIT App Inventor 2 smartphone apps and a microcontroller Arduino ATMEL is used as the main controller and code in Arduino IDE. It has artificial intelligence (AI) capability with ESP32 CAM onboard which has an object classification accuracy of 95.5% using custom Edge Impulse neural network MobileNetV1 96 x 96. This AI capability enhanced the robot’s capability in object classification for grasping.

Center of Pressure Control for Balancing Humanoid Dance Robot Using Load Cell Sensor, Kalman Filter and PID Controller

Balance control on the Lanage Jagad humanoid dance robot is one of the means to create flexible dance movements in the robot movement system to make it more stable and can reduce the frequency of the robot falling or being unable to maintain balance when performing the dance. For the position of the robot, it can use a weight sensor or load cell sensor, the sensor measures the resistance value that can control the weight of 4 weight points on each robot leg which will later be converted into a pressure value at each point, in the study. This test was carried out with the same control behavior using an inertial sensor MPU6050. The balance on the robot uses a balance based on a load cell, which is a situation where the position of the robot in coordinates approaches the center of balance or CoP (Center of Pressure) at coordinates (0,0) or if using MPU6050 it is in a far error value condition so that it can balance the conditions so as not to falls close to the value of the robot state based on ZMP (Zero Moment Point) and CoG (Central of Gravity) as the MPU6050 sensor placement. In this study, for the balance control system using the Arduino MEGA 2560 PRO Board as a complement to the OpenCM 9.04 microcontroller, using 8 load cell sensors to determine the balance point which has been made predictions of pressure from the load cell using a kalman filter also PID control to handle the servo motor. The results from the center point of the robot's pressure have succeeded in determining the center of balance or CoP based on the X coordinates of 0 and the Y coordinates of 0 and the quadrant direction based on the center of gravity, so that the results of the balance system in standing and dancing conditions are based on the center of balance using a load cell, the success rate when standing by 87.5% and balance when dancing by 89%.